Trufle

Trusted Food Waste Control Based on Visual Evidence

Project

TRUFLE aims to employ the blockchain technology and will follow a Self-Sovereign Identity approach, towards increasing the level of trust in the exchange of information among actors of the food supply chain and more specifically in the management and classification of food waste. The Deep Learning based Validation Mechanism (DLVM) will act as a validation mechanism on user generated data (images of food to be wasted) to classify food quantity/quality and enhance the trust on user created content. TRUFLE will provide full auditability, trust and transparency of information reported by retailers, food service providers and consumers about their discarded food and is linked to existing solutions reliably classifying and quantifying the quantity of food waste with the scope of incentivized food-waste reporting. The solution is expected to pave the way for incentivised food reporting mechanisms to trust information from users and link trusted data to food waste reporting incentives.

Goals

  • Support and contribute to food waste management and eventually reduction based on trusted technologies for information exchange between stakeholders and citizens that could also link to incentivized food-waste reporting.
  • Build a Mobile Application incorporating a decentralized Identity wallet to connect with a blockchain infrastructure in the backend and store food waste NFTs (trufleNFTs).
  • Integrate the DLVM with the Blockchain infrastructure to enhance trust and lead to “proof of validity”.

Team

The TRUFLE team includes

Andreas El Saer, Senior Deep Learning Engineer Project Leader

Andreas El Saer (M), Senior Research Engineer (INLECOM) has great experience in Computer Vision and Geospatial domains as well as hands on experience within H2020 projects, in Deep Learning, Image understanding and Software Engineering.

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Harris Niavis: Head of Blockchain Research

Harris Niavis (M), Head of Blockchain Research Stream (INLECOM) has particular research experience since its engagement in Yale University on blockchain, decentralized Identities and IoT and leadership of the design and development of a decentralized platform for off-grid data exchange based on blockchain.

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Konstantinos Loupos: R&D Director

Konstantinos Loupos (M), R&D Director (INLECOM), has extensive experience in embedded systems and sensors and microelectronics systems, security systems, IoT/ICT technologies, DLTs and Cybersecurity. He has participated in >35 EC research projects (since 2000) as Project Coordinator, Technical Manager, Leader of Development teams etc.

Profile photo of Konstantinos Loupos, MEng, MSc, PMP, MBA

Blockchain experience

INLECOM has participated in several H2020 projects as the main blockchain provider, supporting the consortium with secure permissioned blockchain networks, providing in-house custom smart contracts implementations, developing decentralised identity solutions, designing blockchain interoperability architectures or developing innovative applications for diverse business domains. INLECOM’s portfolio includes blockchain-based assets, such as a smart contract generator for SLA management based on HL Fabric, Ethereum-based NFTs for tracking energy emissions, a blockchain interoperability service for increased visibility in the supply chain, an SSI solution based on the HL Aries/Indy stack and a custom in-house integration of Fabric and DIDs.